About the CCL
We design software
that enables our collaborators
to easily harness large scale distributed systems
such as clusters, clouds, and grids. We perform fundamental computer science research
that enables new discoveries through computing in fields such as physics, chemistry, bioinformatics, biometrics, and data mining.
Computational protein folding has historically relied on long-running simulations of single molecules. Although many such simulations can run be at once, they are statistically likely to sample the same common configurations of the molecule, rather than exploring the many possible states it may have. To address this, a team of researchers from the University of Notre Dame and Stanford University designed a system that combined the Adaptive Weighted Ensemble technique to run thousands of short Gromacs and Protomol simulations in parallel with periodic resampling to explore the rich state space of a molecule. Using the Work Queue framework, these simulations were distributed across thousands of CPUs and GPUs drawn from the Notre Dame, Stanford, and commercial cloud providers. The resulting system effectively simulates the behavior of a protein at 500 ns/hour, covering a wide range of behavior in days rather than years.
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- Jesus Izaguirre, University of Notre Dame and Eric Darve, Stanford University